Camera View Blockage Lockout for Networked Machine Security
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Solution Overview
Problem
Existing security camera systems fail to effectively respond to blocked views, which can compromise the functionality and security of network addressable machines by allowing unauthorized access or actions to go unnoticed.
Innovation Solution
Implement a computer-implemented method and system that uses video analytics to detect a blocked view threshold in the field of view of a fixed-location camera, triggering a lockout mode for network addressable machines when a defined percentage of the pixel region is obstructed, ensuring the machines enter a secure state.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If security cameras are installed to monitor network addressable machines, then security monitoring capability is improved, but the system cannot respond effectively when views are blocked, compromising security
Solution Approach 1:
The system implements feedback by continuously analyzing video feed from security cameras and automatically responding to blocked view conditions. When the video analytics system detects that a predefined portion of the camera field of view is obstructed, it triggers an alert and can initiate lockout protocols for the monitored network addressable machine, creating a closed-loop security response system
Solution Approach 2:
The patent introduces video analytics software as an intermediary between the security camera system and the network addressable machines. This intermediary layer processes video data, detects blocked views, and communicates with both the camera system and the monitored machines, enabling intelligent security responses without direct mechanical intervention
2Reliability
If video analytics are used to detect blocked views, then security response effectiveness is improved, but system complexity increases
Solution Approach 1:
The video analytics system is designed to perform multiple functions: it monitors for blocked views, identifies potential security threats, tracks objects and persons in the field of view, and generates alerts. By consolidating these diverse security functions into a single analytics platform, the system improves security response effectiveness while managing complexity through functional integration rather than proliferation of separate systems
3Object-affected harmful factors
If lockout mode is triggered automatically upon blocked view detection, then security protection is improved, but operational convenience deteriorates
Solution Approach 1:
The system applies preliminary anti-action by implementing a graduated response to blocked views. Rather than immediately locking out machines, the system first generates alerts and notifications, giving operators an opportunity to address the blocked view condition. Lockout mode is triggered only if the blocked view condition persists or if multiple alerts are generated, thereby preventing unauthorized access while minimizing unnecessary operational disruptions
Data Source
AI summary
A method and system for a lockout in response to a blocked view is disclosed. The method is carried out within at least one network. The at least one network includes at least one network addressable machine and at least one fixed-location camera having a respective Field Of View (FOV). The method includes creating an operation dependency definition between the fixed-location camera and the network addressable machine based on an inclusion of the network addressable machine within the FOV. Video analytics is employed to generate a blocked view alert in response to a blocked view threshold being satisfied in relation to the live video captured by the fixed-location camera. In response to the blocked view alert, the network addressable machine is caused to enter a lockout mode.